The present invention relates to object segmentation in medical images, and more particularly to evaluating image segmentation based on visibility.
Angiography is a medical imaging technique in which X-ray images are used to visualize internal blood filled structures, such as arteries, veins, and the heart chambers. Since blood has the same radiodensity as the surrounding tissues, these blood filled structures cannot be differentiated from the surrounding tissue using conventional radiology. Thus, in angiography, a contrast agent is added to the blood, usually via a catheter, to make the blood vessels visible via X-ray. In many angiography procedures, X-ray images are taken over a period of time, which results in a sequence of fluoroscopic images, which show the motion of the blood over the period of time. Such fluoroscopic image sequences contain useful information that can be difficult to decipher due to the collapsing of 3-dimensional information into the 2-dimensional images.
Since different objects in a fluoroscopic image sequence have different patterns of motion, objects can be extracted from a fluoroscopic image sequence in layers based on motion patterns found in the fluoroscopic image sequence. Coronary digital subtraction angiography (DSA) is a method for segmenting vessels in the heart by extracting motion-based layers from fluoroscopic image sequences of the heart. Coronary DSA separates the vessels from background in the fluoroscopic images, such that the segmented vessels are highly visible. Although human perception can be used to see that the visibility of the segmented vessels has increased, there is no quantitative measurement of visibility that can be used to evaluate segmentation techniques.